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Proposal for Measuring Quality of Decision Trees Partition

Proposal for Measuring Quality of Decision Trees Partition

Souad Taleb Zouggar, Abdelkader Adla
Copyright: © 2017 |Volume: 9 |Issue: 4 |Pages: 21
ISSN: 1941-6296|EISSN: 1941-630X|EISBN13: 9781522512585|DOI: 10.4018/IJDSST.2017100102
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MLA

Zouggar, Souad Taleb, and Abdelkader Adla. "Proposal for Measuring Quality of Decision Trees Partition." IJDSST vol.9, no.4 2017: pp.16-36. http://doi.org/10.4018/IJDSST.2017100102

APA

Zouggar, S. T. & Adla, A. (2017). Proposal for Measuring Quality of Decision Trees Partition. International Journal of Decision Support System Technology (IJDSST), 9(4), 16-36. http://doi.org/10.4018/IJDSST.2017100102

Chicago

Zouggar, Souad Taleb, and Abdelkader Adla. "Proposal for Measuring Quality of Decision Trees Partition," International Journal of Decision Support System Technology (IJDSST) 9, no.4: 16-36. http://doi.org/10.4018/IJDSST.2017100102

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Abstract

To compute a partition quality for a decision tree, we propose a new measure called NIM “New Information Measure”. The measure is simpler, provides similar performance, and sometimes outperforms the existing measures used with tree-based methods. The experimental results using the MONITDIAB application (Taleb & Atmani, 2013) and datasets from the UCI repository (Asuncion & Newman, 2007) confirm the classification capabilities of our proposal in comparison to the Shannon measure used with ID3 and C4.5 decision tree methods.

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